Preprint / Version 1

Discovery of potent inhibitors of rumen methane metabolism via an AI-assisted workflow

This article is a preprint and has not been certified by peer review.

Authors

    Xiong Xia,  
    Xiong Xia
    • 中科院深圳先进技术研究院
    • Shenzhen Institutes of Advanced Technology image/svg+xml
    Liangzhen Zheng,   Jinjie Zhou,   Haoran Ni,   Guoliang Zhu,   Hongbin Liu,   Ruiyue Chen,   Haimei Shi,   Huizeng Sun,   Meng Li,  
    Meng Li
    Sheng Wang,  
    Sheng Wang
    • Shanghai Zelixir Biotech Co. Ltd
    Lei Dai
    Lei Dai
Categories
Biology x AI
Keywords
Artificial Intelligence; Methane Mitigation; Methanogen; Virtual Screening; Rumen Microbiome

Abstract

Ruminant methane emission has attracted increasing attention due to its significance in global climate change and sustainable livestock production. Methyl-coenzyme M reductase (MCR), the key enzyme involved in the terminal step of methanogenesis in the rumen microbiome, is responsible for nearly all biologically generated methane released into the atmosphere. In this study, we developed an AI-assisted workflow for discovery of novel MCR inhibitors. Ultra-fast virtual screening of ~23 million molecules yielded 26 candidate molecules for experimental validation, among them 4 molecules showed significant inhibition of methane metabolism. Subsequent structure-guided optimization led to the discovery of a sub-nanomolar inhibitor Pyrazol-5(4H)-one,3-(4-nitrophenyl) (PZON), which effectively suppressed methane production in rumen microbiome fermentation and exhibited minimal cytotoxicity. Overall, our study provides promising candidates for methane-reducing feed additives, and demonstrates the power of AI-assisted discovery of small molecules for targeted modulation of gastrointestinal microbiomes.

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DOI:

https://doi.org/10.65215/LTSpreprints.2026.02.28.000144

Submission ID:

144

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Posted

2026-02-28

How to Cite

Xia, X., Zheng, L., Zhou, J., Ni, H., Zhu, G., Liu, H., Chen, R., Shi, H., Sun, H., Li, M., Wang, S., & Dai, L. (2026). Discovery of potent inhibitors of rumen methane metabolism via an AI-assisted workflow. LangTaoSha Preprint Server. https://doi.org/10.65215/LTSpreprints.2026.02.28.000144

Declaration of Competing Interests

Details of all competing interests to be disclosed are as follows:

L.D. is the cofounder of SynBiome Biotech, Ltd. S.W. and L. Z. are the cofounders of Zelixir Biotech Co., Ltd. The authors have filed patent applications on small molecule inhibitors reported in this paper.

Copyright

The copyright holder for this preprint is the author/funder.

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.